Ant Behavior and Transportation Networks

What do ant colonies and railroad systems have in common? Both serve to transport goods and individuals from place to place, and need to balance the often competing goals of doing so efficiently and at low cost, while also remaining robust to potential disruptions to the network. We are currently working to understand how simple organisms can work together in groups to create and maintain such transportation networks, using a multidisciplinary combination of field and laboratory experiments with turtle ants, along with mathematical and computational models.

A key part of this work is testing the behavior of turtle ants in laboratory experiments. How do individual ants explore branching tree-like structures as they search for food and nesting resources? Do ants communicate about their discoveries, either indirectly via pheromones or directly by following one another? How do groups of ants choose new nests and create pathways for transporting resources between them? Over the summer, we ran a set of experiments designed to test these questions. Students beginning in the lab this semester will (1) care for ants in the lab, (2) record data from videos taken of those experiments, and/or (3) design and carry out small follow-up experiments.

Name of research group, project, or lab
HMC Bee Lab
Why join this research group or lab?

You will be part of a team of students working on a set of related interdisciplinary projects, using mathematics, computation and engineering to solve problems of biological interest. The variety of techniques and approaches will give you an opportunity to explore your interests and develop new skills. The project is part of a larger NSF-funded collaborative research project, so you will interact with a larger research group including graduate students and postdoctoral researchers at George Washington University and the University of York. There may be opportunities to continue the work in a senior thesis, present at a regional or national conference, and/or co-author future publications stemming from ongoing work.

Logistics Information:
Project categories
Data Science
Student ranks applicable
Student qualifications

No prior background or experience is required! Students should have an interest in the complexity of the natural world and potentially in the application of quantitative tools and models to understand it. First and second-year students still exploring their interests are encouraged to apply.

Time commitment
Fall - Part Time
Academic Credit
Number of openings
Techniques learned

Students will learn to care for ants in the laboratory. Depending on background and interest, they may also learn about experimental design and/or data analysis and visualization in R. Students will learn to read and discuss scientific literature, and to communicate across disciplinary boundaries and with the public about their work.

Contact Information:
Mentor name
Matina Donaldson-Matasci
Mentor email
Mentor position
Associate Professor of Biology
Name of project director or principal investigator
Matina Donaldson-Matasci
Email address of project director or principal investigator
1 sp. | 8 appl.
Hours per week
Fall - Part Time
Project categories
Biology (+1)
BiologyData Science